Recommendation systems have two parts, generator and recommendation engine. The generator creates the recommendations. It lists N, usually 20, recommended items (or users) for each target item (user). It can be manual entry, but is usually an automated system using correlation, Bayesian, or neural networks to relate items based upon user actions. The recommendation engine receives requests for recommendations, and returns the recommended items. The request usually includes the number of desired recommendations and type of recommendations (cross-sell, similar, or personal).
There are numerous examples in the prior art, including patent application Ser. No. 12/764,091 (publication US 2010-0268661 A1) entitled “Improvements in Recommendations Systems” by Ken Levy and Neil Lofgren, patent application Ser. No. 13/107,858 (publication US 2011-0282821 A1) entitled “Further Improvements in Recommendation Systems” by Ken Levy and Neil Lofgren, and patent application Ser. No. 13/492,859 (publication US 2012-0316986 A1) entitled “More Improvements in Recommendation Systems” by Ken Levy and Neil Lofgren, all incorporated herein by reference.
Recommendation solutions are not used for inside sales since most sales tools don't have the customer behavior required to create recommendations. The recommendations would help the salesperson suggest products to the prospect. In addition, it is difficult to create accurate recommendations for new products or products with few sales. Furthermore, prospects now shop online via computers, tablets and phones, as well as in-store via mobile apps. It's ideal to recognize them across these channels. The in-store apps are currently custom developed and expensive. Recommendations are currently served to point-of-sale solutions during payment, which can be too late. Recommendations should be personal based upon shopper's preferences and shopper's characteristics. Market places can be used for customer acquisition.
Furthermore, websites are expensive to build and maintain. They require expensive technical resources, especially mobile and responsive websites. Websites are critical today, especially mobile sites with the penetration of smart phones.